Front

What is an alternative hypothesis?

Back

An alternative hypothesis is a statement that suggests a potential outcome or effect, indicating that there is a relationship between variables. For example, 'The COVID vaccine reduces the chances that one will get COVID.'

Front

What is the purpose of calculating degrees of freedom in statistical analysis?

Back

Calculating degrees of freedom helps to determine the critical value in hypothesis testing, taking into account the sample size of the experiment.

Front

What is the null hypothesis?

Back

The null hypothesis is the assumption that there is no relationship or effect between the two variables being studied.

Front

What type of t-test is used when comparing the same group of students' GPAs before and after an intervention?

Back

A dependent t-test is used when comparing the same group of subjects under different conditions.

Front

What does it mean if the t-statistic is higher than the critical value?

Back

If the t-statistic is higher than the critical value, the data is considered significant, and we reject the null hypothesis.

Front

Define the term 'critical value' in hypothesis testing.

Back

The critical value is a threshold that determines whether to reject the null hypothesis, based on the chosen significance level.

Front

What is a p-value in statistical analysis?

Back

A p-value is the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.

Front

Explain the difference between independent and dependent variables.

Back

Independent variables are manipulated or changed in an experiment, while dependent variables are measured to see if they are affected by changes in the independent variable.

Front

What is the significance level (alpha) in hypothesis testing?

Back

The significance level (alpha) is the probability of rejecting the null hypothesis when it is actually true, commonly set at 0.05.

Front

What does it mean to 'fail to reject' the null hypothesis?

Back

Failing to reject the null hypothesis means that there is not enough evidence to support the alternative hypothesis.